Database driven computer systems and computer-implemented methods for attributing in real-time web originated activities to media events and tracking the performance thereof

ABSTRACT

In some embodiments, the present invention is directed to a computer system which includes: a specifically programmed server, where the server includes a plurality of modules configured to perform at least: electronically and periodically obtaining, over a computer network, media data from a plurality of computer systems of media data sources, where the media data is associated with a plurality of media airings of a plurality creatives; electronically and periodically obtaining web tracking transaction data from a computer system of a web tracking electronic source; where the web tracking transaction data including web tracking metrics for web originated activities; where web originated activities include web orders placed in response to the offer associated with the creative; for each web order record in the transactional web data: attributing, by the specifically programmed server, a particular web order to a particular media airing; and displaying a real time updatable web attribution report.

RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.15/012,595, entitled “DATABASE DRIVEN COMPUTER SYSTEMS ANDCOMPUTER-IMPLEMENTED METHODS FOR PROCESSING REAL-TIME ATTRIBUTION OF WEBORIGINATED ACTIVITIES TO MEDIA AGENCY RECORDS AND TRACKING THEREOF”,filed Feb. 1, 2016 which is a continuation of U.S. patent applicationSer. No. 14/736,017, entitled “DATABASE DRIVEN COMPUTER SYSTEMS ANDCOMPUTER-IMPLEMENTED METHODS FOR PROCESSING REAL-TIME ATTRIBUTION OF WEBORIGINATED ACTIVITIES TO AIRINGS AND TRACKING THEREOF”, filed Jun. 10,2015, which is incorporated herein by reference in its entirety for allpurposes.

TECHNICAL FIELD

In some embodiments, the present invention generally relates to databasedriven computer systems and computer-implemented methods for processingreal-time attribution of web originated activities to airings andtracking thereof.

BACKGROUND

For example, in the realm of Direct Response Television (DRTV), amarketer makes an offer to the viewer to purchase or to inquire about apackage of products or services, or to pledge a donation, by visiting aspecific URL through individual broadcast airings of a paid commercialprogram of 28:30 in length (infomercial) or a commercial message ofvarying lengths equal to or less than five minutes.

BRIEF SUMMARY

In some embodiments, the present invention is directed to a computersystem which includes at least the following components: at least onespecifically programmed server; at least one non-transitory webattribution database accessible by the at least one specificallyprogrammed server, where the at least one web attribution database isspecifically programmed to be dedicated for use by the at least onespecifically programmed server; where the at least one specificallyprogrammed server comprises a plurality of modules configured to performat least the following operations: electronically and periodicallyobtaining, over the computer network, by a media data programmedcomputer interface module of the at least one specifically programmedserver, media data from a plurality of computer systems of media datasources, where the media data is associated with a plurality of mediaairings of a plurality creatives; electronically and periodicallyobtaining, over a computer network, by a web data programmed computerinterface module of the at least one specifically programmed server, webtracking transaction data from a computer system of at least one webtracking electronic source; where the web tracking transaction dataincluding web tracking metrics for web originated activities for atleast one website associated with at least one offer of at least onecreative; where web originated activities comprise web orders placed inresponse to the at least one offer associated with the at least onecreative; for each web order record in the transactional web data: basedon an item identifier of at least one item and a price of the at leastone item corresponding to a particular web order corresponding to suchweb order record, determining, the at least one specifically programmedserver, at least one particular offer associated with the particular weborder, based on the at least one particular offer, determining, the atleast one specifically programmed server, a length of a creative whichhas used for promoting the at least one item; based on the particularoffer, identifying, the at least one specifically programmed server, asubset of media agency records in the media data which are potentiallyattributable to such particular web order; adjusting, the at least onespecifically programmed server, a time of airing for each record in thesubset of media agency records based on at least one of: i) apredetermined uniform time zone, and ii) an IP address associated withthe web order, and iii) a geographic location of a web host at which theparticular web order was placed; based on the length of the creative,selecting, the at least one specifically programmed server, a firstsubgroup of media agency records from the subset of media agencyrecords, where the length of the creative corresponds to a predeterminetime window, where the predetermined time window ends at the time of theparticular web order, and continues in the past for a predetermined timeduration; based on an IP address of the particular web order from thetransactional web data, selecting, the at least one specificallyprogrammed server, a second subgroup of media agency records from thefirst subgroup of media agency records, where the second subgroup ofmedia agency records correspond to media airings shown in a geographiclocality of the particular web order; determining, by the at least onespecifically programmed server, for each media airing of the secondsubgroup, a probability of attribution based on cost of such mediaairing or viewership rating; based on the probability of attribution,duplicating, by the at least one specifically programmed server, aparticular media airing record of the second subgroup X times in thededicated database to obtain a third subgroup, where X is a whole numberbased on rounding the probability of attribution; assigning, by the atleast one specifically programmed server, to each record in the thirdsubgroup a random value within a predetermined number range between Y1and Y2, where Y2 is larger than Y1; based on the random value, ranking,by the at least one specifically programmed server, each record in thethird subgroup so that a particular media airing having the random valuewhich is the closest to Y2 is assigned the highest rank; attributing, bythe at least one specifically programmed server, the particular weborder to the particular media airing having the highest rank; anddisplaying, the at least one specifically programmed server, utilizingat least one graphical user interface, a real time updatable webattribution report.

In some embodiments, the at least one specifically programmed server isfurther configured to: electronically and real-time obtain, by afulfillment data programmed computer interface module of the at leastone specifically programmed server, from a computer system of at leastone fulfillment electronic source, fulfillment transaction data; wherethe fulfillment transaction data including a plurality of at leastthousand fulfillment records associated a plurality of at least thousandfulfillment transactions for the web orders; where each fulfillmentrecord identifies each fulfillment transaction being associated with aparticular web order; and matching, in real-time, records between webrecords and fulfillment records based, at least in part, on: i) an orderdate, ii) a 5 digit Zip code, iii) a last name, iv) an order amount, andv) optionally, a street name.

In some embodiments, the at least one web tracking electronic source isselected from the group consisting of: Piwik, Google Analytics, andOmniture.

In some embodiments, the length of the creative corresponds to thepredetermine time window based on the following rules: i) when thelength of the creative is between 15 and 30 seconds, the predeterminedtime window is 30 minutes, ii) when the length of the creative isbetween 60 and 120 seconds, the predetermined time window is 2 hours,iii) when the length of the creative is 5 minutes, the predeterminedtime window is 4 hours, and iv) when the length of the creative is 28minutes and 30 seconds, the predetermined time window is 8 hours. Insome embodiments, Y1 is 0, and Y2 is 1. In some embodiments, the randomvalue is generated by a random value generator. In some embodiments, thepredetermined time zone is selected from the group consisting of: U.S.Eastern time zone, U.S. Central time zone, and U.S. Western time zone.

In some embodiments, the media airing is an airing which is selectedfrom the group consisting of: a television station airing, a radiostation airing, a video-on-demand airing, a web-promoted offer airing,and a mobile message airing. In some embodiments, the viewership ratingis Nielsen rating.

In some embodiments, the present invention is directed to acomputer-implemented method which includes at least the following steps:electronically and periodically obtaining, over the computer network, bya media data programmed computer interface module of the at least onespecifically programmed server, media data from a plurality of computersystems of media data sources, where the media data is associated with aplurality of media airings of a plurality creatives; electronically andperiodically obtaining, over a computer network, by a web dataprogrammed computer interface module of the at least one specificallyprogrammed server, web tracking transaction data from a computer systemof at least one web tracking electronic source; where the web trackingtransaction data including web tracking metrics for web originatedactivities for at least one website associated with at least one offerof at least one creative; where web originated activities comprise weborders placed in response to the at least one offer associated with theat least one creative; for each web order record in the transactionalweb data: based on an item identifier of at least one item and a priceof the at least one item corresponding to a particular web ordercorresponding to such web order record, determining, the at least onespecifically programmed server, at least one particular offer associatedwith the particular web order, based on the at least one particularoffer, determining, the at least one specifically programmed server, alength of a creative which has used for promoting the at least one item;based on the particular offer, identifying, the at least onespecifically programmed server, a subset of media agency records in themedia data which are potentially attributable to such particular weborder; adjusting, the at least one specifically programmed server, atime of airing for each record in the subset of media agency recordsbased on at least one of: i) a predetermined uniform time zone, and ii)an IP address associated with the web order, and iii) a geographiclocation of a web host at which the particular web order was placed;based on the length of the creative, selecting, the at least onespecifically programmed server, a first subgroup of media agency recordsfrom the subset of media agency records, where the length of thecreative corresponds to a predetermine time window, where thepredetermined time window ends at the time of the particular web order,and continues in the past for a predetermined time duration; based on anIP address of the particular web order from the transactional web data,selecting, the at least one specifically programmed server, a secondsubgroup of media agency records from the first subgroup of media agencyrecords, where the second subgroup of media agency records correspond tomedia airings shown in a geographic locality of the particular weborder; determining, by the at least one specifically programmed server,for each media airing of the second subgroup, a probability ofattribution based on cost of such media airing or viewership rating;based on the probability of attribution, duplicating, by the at leastone specifically programmed server, a particular media airing record ofthe second subgroup X times in the dedicated database to obtain a thirdsubgroup, where X is a whole number based on rounding the probability ofattribution; assigning, by the at least one specifically programmedserver, to each record in the third subgroup a random value within apredetermined number range between Y1 and Y2, where Y2 is larger thanY1; based on the random value, ranking, by the at least one specificallyprogrammed server, each record in the third subgroup so that aparticular media airing having the random value which is the closest toY2 is assigned the highest rank; attributing, by the at least onespecifically programmed server, the particular web order to theparticular media airing having the highest rank; and displaying, the atleast one specifically programmed server, utilizing at least onegraphical user interface, a real time updatable web attribution report.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention can be further explained with reference to theattached drawings, wherein like structures are referred to by likenumerals throughout the several views. The drawings shown are notnecessarily to scale, with emphasis instead generally being placed uponillustrating the principles of the present invention. Further, somefeatures may be exaggerated to show details of particular components. Inaddition, any measurements, specifications and the like shown in thefigures are intended to be illustrative, and not restrictive. Therefore,specific structural and functional details disclosed herein are not tobe interpreted as limiting, but merely as a representative basis forteaching one skilled in the art to variously employ the presentinvention.

FIG. 1 depicts a block diagram of an exemplary system 100 in accordancewith one or more embodiments.

FIG. 2 depicts an exemplary architecture for implementing a computingdevice in accordance with one or more embodiments.

FIGS. 3-9 depict certain aspects of the present invention in accordancewith some embodiments.

DETAILED DESCRIPTION

Among those benefits and improvements that have been disclosed, otherobjects and advantages of this invention will become apparent from thefollowing description taken in conjunction with the accompanyingfigures. Detailed embodiments of the present invention are disclosedherein; however, it is to be understood that the disclosed embodimentsare merely illustrative of the invention that may be embodied in variousforms. In addition, each of the examples given in connection with thevarious embodiments of the invention which are intended to beillustrative, and not restrictive.

Throughout the description, the following terms take the meaningsexplicitly associated herein, unless the context clearly dictatesotherwise. The phrases “in one embodiment” and “in some embodiments” asused herein do not necessarily refer to the same embodiment(s), thoughit may. Furthermore, the phrases “in another embodiment” and “in someother embodiments” as used herein do not necessarily refer to adifferent embodiment, although it may. Thus, as described below, variousembodiments of the invention may be readily combined, without departingfrom the scope or spirit of the invention.

In addition, as used herein, the term “or” is an inclusive “or”operator, and is equivalent to the term “and/or,” unless the contextclearly dictates otherwise. The term “based on” is not exclusive andallows for being based on additional factors not described, unless thecontext clearly dictates otherwise. In addition, throughout thespecification, the meaning of “a,” “an,” and “the” include pluralreferences. The meaning of “in” includes “in” and “on.”

It is understood that at least one aspect/functionality of variousembodiments described herein can be performed in real-time anddynamically. As used herein, the term “real-time” means that anevent/action can occur instantaneously or almost instantaneously in timewhen another event/action has occurred.

As used herein, the terms “dynamic(ly)” and “automatic(ly)” mean that anevent/action that can occur without any human intervention. In someembodiments, the event/action may be in real-time and/or hourly, daily,weekly, monthly, annually, etc.

In describing and illustrating the exemplary embodiments, specificterminology is employed for the sake of clarity. However, theembodiments are not intended to be limited to the specific terminologyso selected. A person skilled in the relevant art will recognize thatother components and configurations may be used without parting from thespirit and scope of the embodiments. It is to be understood that eachspecific element includes all technical equivalents that operate in asimilar manner to accomplish a similar purpose. The examples andembodiments described herein are non-limiting examples.

As used herein, the term “creative” means a commercial, publishedelement, display, link and/or advertisement that a consumer sees. Forexample, for TV, the creative can be an Infomercial or Short Form spots,format lengths (:30/:60/:120) could be interchangeable as a singularcreative or they could be separate creatives.

As used herein, the term “offer” represents a particular Product/Serviceconfiguration or a package of Products/Services, and/or pricing schemerelative to a specific creative, media agency and/or upsellconfiguration strategy.

As used herein, the terms “web originated activity” and “web originatedactivities” represent including, but not limited to, calls, leads,orders, SMS texts, visits, votes, pledges, emails, mail, etc.

As used herein, the term “media source” represents a source, host and/orprovider of electronic data regarding an airing (also referenced here asa media airing) which is a media event involving a creative which hasbeen shown/distributed via one or more media outlets, including, but notlimited to, TV Stations, Radio Stations, Web Channels/Sites (e.g.,youtube.com's channels(s)), Social Sites, Internet streaming (such asservice provided by Roku), Satellite, On Demand, emails, mail,publications, inserts, circulars, etc. For example, Roku utilizes astreaming player (or simply Roku) which is a set-top box manufactured byRoku, Inc. Typically, Roku partners provide over-the-top content in theform of channels. As used herein, a particular media event correspondingto a particular airing/media airing is an event that can be defined bytime, date, and length parameters. In some embodiments, the media airingis an airing which is selected from the group consisting of: atelevision station airing, a radio station airing, a video-on-demandairing, a web-promoted offer airing (e.g., banner ads), a mobile messageairing (e.g., mobile SMS, email, etc.).

As used herein, the term “campaign” is directed to a set and/or groupingof Creatives targeting a particular marketing effort and/or event. Forexample, creatives within a campaign can be single or omni-channel.

In some embodiments, an advertisement, creative, is designed to induceconsumers to engage in web originated activity(ies).

In some embodiments, a unique airing can be recorded in a database as arecord identifying a network or station, day of week and local time.

In some embodiments, the inventive computer systems of the presentinvention are configured to continuously attribute, in real-time, weboriginated activities to airings via Direct Response Television (DRTV)(e.g., individual broadcast airings (such as a paid commercial programof 28:30 in length (infomercial)); a series of airings between one andfive minutes in which a marketer makes an offer to the viewer topurchase a product, a package of products, a service, or both; 30seconds commercials, etc.) which asks viewers to visit a specificinternet address (e.g., URL, URL encoded 3D barcode, etc.). In someembodiments, the inventive computer systems of the present invention areconfigured to receive data regarding every airing that is tracked, forexample but not limited to, in terms of the TV network/station it ran,day, time, calls, orders, and/or revenue it produced.

Illustrative Example in Accordance with Some Embodiments of the PresentInvention when the Web Originated Activity is an Order

In some embodiments, the media data is media agency data and at leastone media source is an electronic computer system of a particular mediaagency. In some embodiments, the media agency can be an advertisingagency, a network, a station, or any other suitable entity that places,distributes, and/or publishes creatives.

In some embodiments, the inventive computer systems of the presentinvention are configured to receive, from various media sources,contracted by or on behalf of a marketer (e.g., producer of products orprovider of services), media data regarding airings. In someembodiments, the inventive computer systems of the present invention areconfigured to verify the incoming data and to populate a media datatable in a non-transitory database. In some embodiments, the inventivecomputer systems of the present invention are, similarly, configured toreceive and process web data regarding web originated activities (e.g.,orders placed on the internet).

In some embodiments, the inventive systems of present invention areconfigured to process records associated with at least 1 to 1,000marketers. In some embodiments, the inventive systems of presentinvention are configured to process records associated with at least1,000 to 10,000 marketers. In some embodiments, the inventive systems ofpresent invention are configured to process records associated with atleast 10,000 to 100,000 marketers. In some embodiments, the inventivesystems of present invention are configured to process recordsassociated with at least 100,000 marketers.

In some embodiments, the inventive systems of present invention areconfigured to process records associated with at least 1 to 1,000creatives. In some embodiments, the inventive systems of presentinvention are configured to process records associated with at least1,000 to 10,000 creatives. In some embodiments, the inventive systems ofpresent invention are configured to process records associated with atleast 10,000 to 1,000,000 creatives. In some embodiments, the inventivesystems of present invention are configured to process recordsassociated with at least 1,000,000 to 1,000,000,000 creatives. In someembodiments, the inventive systems of present invention are configuredto process records associated with at least 1,000,000,000 creatives.

In some embodiments, the inventive systems of present invention areconfigured to process records associated with at least 1 to 1,000 mediaoutlets. In some embodiments, the inventive systems of present inventionare configured to process records associated with at least 1,000 to10,000 media outlets. In some embodiments, the inventive systems ofpresent invention are configured to process records associated with atleast 10,000 to 1,000,000 media outlets. In some embodiments, theinventive systems of present invention are configured to process recordsassociated with at least 1,000,000 media outlets.

Exemplary Web Tracking/Analytics Databases (Piwik, GA, Omniture, Etc.)

In some embodiments, the inventive systems of the present inventioncombine and validate data for web originated activity records (e.g.,records of web placed orders) from a plurality of web tracking sourcesvia, for example, ETL (Extract, Transform, Load)-type processes on, forexample, a periodical basis (e.g., Daily Transactional File—24 Hrs.). Insome embodiments, the web data is processed in real time through anattribution process that matches web originated activity records toactive offers based on a particular SKU (i.e., a stock identificationunit such as product or service identification code) and/or acombination of a pre-determined number of SKUs associated with each weboriginated activity record (e.g., a single item web order record wouldinclude a single SKU code). For example, a unique KitCode identifier fora particular active offer is recorded in a particular field in adatabase table and represents two or more SKUs based on an associationtable between the unique KitCode identifier and the two or more SKUs.

Exemplary Web Attribution Data Processing Based, at Least in Part, atLeast One Source of Web Originated Activity Data Analytics

In some embodiments, the inventive systems of the present inventionperforms web attribution processing utilizing a single electronic datasource for web originated activity data analytics. In some embodiments,the single electronic data source for web originated activity dataanalytics can be selected from the group of Piwik (www.piwik.org),Omniture/Adobe Marketing Cloud(http://www.adobe.com/marketing-cloud.html), Premium Google Analytics(http://www.google.com/analytics/premium/), and any other similarlysuitable electronic data source for web originated activity dataanalytics. The specific web tracking protocols and correspondingspecific data structures of each of the above identified electronic datasources, including any of their future modifications, as at leastdescribed at identified web locations, are hereby incorporated byreferences in their entirety for such purpose.

In some embodiments, an exemplary data structure for web originatedactivity data analytics of a particular electronic data source can havethe following fields: Data Provider, Client, Landing Page URL, OrderNumber, Order Date, Order Time, Time zone, Disposition, Referral Type,Referral URL, # of Pages Viewed, Time On Website, Bounce Rate, ShoppingCart Status, Max Items in Shopping Cart, Email Address, Date of Landing,Time of Landing, Browser, Device Name, Webuser Country, Webuser State,Webuser City, Items in Cart at Checkout, # of Unique Visits in the Past,Billing Name First, Billing Name Last, Billing Address 1, BillingAddress 2, Billing City, Billing State/Province, Billing Country,Billing ZIP/Postal Code, Billing Phone Number, Offer Code, ShippingPrice, Merchandise Price, Order Tax, Order Discount, Order Total,Payment Method, Age, Gender, Shipping Name First, Shipping Name Last,Shipping Address 1, Shipping Address 2, Shipping City, ShippingState/Province, Shipping ZIP/Postal Code, Shipping Country, ShippingPhone Number, Shipping Method, Currency, IP Address, Custom String, WebAnalytic Provider, Item 1 SKU, Item 1 Price, Item 1 Quantity, Item 1Shipping price, Item 1 Indicator Code, Item 1 Discount.

In some embodiments, the inventive systems of the present inventionelectronically receives web originated activity tracking data from aparticular electronic data source (e.g., Piwik). In some embodiments,the inventive systems of the present invention can utilize, for example,a value in a field of “Order ID” to automatically, in real time, verifythat the associated web originated activity record is valid. In someembodiments, if the inventive systems of the present inventiondetermines that the Order ID is valid, the inventive systems of thepresent invention then accepts such web originated activity record forfurther processing. In some embodiments, any unmatched records can beseparately stored in a database until the matching failure is resolved.

In some embodiments, the inventive systems of the present invention canutilize data of a particular web order to match such record to aparticular active offer (e.g., a creative identifies a website on whichcustomers can order product(s)/service(s) based on the particular activeoffer). In some embodiments, the inventive systems of the presentinvention can utilize a value for the matched web offer to identifyproduct(s)/service(s) (e.g., based on SKU code(s)), and a media length(e.g., a length of creative/commercial). For instance, in someembodiments, the inventive systems of the present invention can utilizeautomatic lookup from a list of offers to identify the particular activeoffer.

In some embodiments, the inventive systems of the present invention thentags/flags each record of web originated activity records as being:attributable or non-attributable. In some embodiments, the inventivesystems of the present invention can then generate a report (e.g., anelectronic output) of non-attributable web originated activity recordsfor further actions such as automatic discovery and correction oferrors.

In some embodiments, if needed, the inventive systems of the presentinvention then performs time adjusting to a particular single uniformtime zone.

For example, if the attributably tagged records obtained from a weboriginated activity data analytics source are already time stamped basedon the desired single uniform time zone, then no further time adjustmentis needed.

In other scenarios, for example, if the desired single uniform time zoneis the U.S. Eastern time zone and the attributably tagged recordsobtained from a web originated activity data analytics source whoseservers log transactions based on the Western time zone in respect tothe main time zones of the U.S., or log records in two or more differenttime zones, then the inventive systems of the present invention wouldprocess the attributable web records to be adjusted to the desiredsingle uniform time zone. In some embodiments, the inventive systems ofthe present invention can use geographic location(s) of where the webdata analytics source is located to, automatically and in real time,determine the particular single uniform time zone to which allattributable records need to be adjusted. In some embodiments, theinventive systems of the present invention can utilize one or more ofthe following parameters to synchronize/adjust to a single uniform timezone (e.g., the U.S. Eastern time zone) airing records, the attributableweb originated activity records, or both.

Media Airing Time & Local Time Parameters

In some embodiments, the inventive systems of the present invention can,for example, adjust the airing records (e.g., media agency responserecords (MARs)) based on a time zone in which a particular airing of theparticular creative associated with the particular offer wasshown/distributed. For instance, if the desired uniform time zone forsynchronizing the airing records and the web originated activity recordsis the U.S. Eastern time zone, and the airing was shown at 9 A.M.Western Standard Time (WST), the airing time is adjusted to 12 P.M.Eastern Standard Time (EST) in the airing record. If there are twoairings in two different time zones (e.g., a 1^(st) airing at 9 AM ESTand a 2^(nd) airing at 9 AM WST), the inventive systems of the presentinvention can generate a secondary host airing record having the airingtime based on the first airing (e.g., 9 AM EST) and the secondary hostairing (12 PM EST).

IP Address of a Computer Device Associated with the Web OriginatedActivity (e.g., Order)

In some embodiments, the inventive systems of the present invention canutilize IP addresses from the web originated activity records todetermine if there is a need for time adjustment of the airing records,the web originated activity records (e.g., web order records), or both.In some embodiments, the inventive systems of the present invention canutilize a suitable IP address mapping tool to determine a time zoneassociated with the particular IP address.

Web Host Location

In some embodiments, the inventive systems of the present invention canidentify a geographic location of a web host that is hosting a webpageto which customers are directed by the campaign's airings for placingtheir orders to determine if there is a need for time adjustment of theairing records, the web originated activity records (e.g., web orderrecords), or both.

After the time adjustment operation(s), if such is needed, in someembodiments, the inventive systems of the present invention would have adataset of all media airings associated with the particular offer whereall times are adjusted to the same time zone. In some embodiments, theinventive systems of the present invention then selects a particularpre-determined time reference window (i.e., a time period ending at thetime of the web order and starting at a pre-determined time prior to theweb order time) to identify media airings based on length, such as, butis not limited to:

:15/:30-30 Minute Window

:60/:120-2 Hour Window

5 Min-4 Hour Window

28:30-8 Hour Window.

In some embodiments, the inventive systems of the present invention canautomatically and in real time select the particular time window and/ora user can utilize at a specifically programmed user graphical interfaceto select/adjust particular time window. For instance, FIG. 3 shows oneexample when the 8 hour time window has been applied to identifyparticular media airings for a particular order placed at P.M., asrecorded in Piwik data. In some embodiments, the inventive systems ofthe present invention can automatically and in real time group mediaairing records based on two or more pre-determined time windows due todifferent time lengths for airing particular creative(s).

In some embodiments, the inventive systems of the present invention canselect the particular time window and/or a user can utilize at aspecifically programmed user graphical interface to select/adjustparticular time window. For instance, FIG. 4 shows other examples ofother time windows applied based on the length of media airings.

After the group(s) of media airings is/are identified, in someembodiments, the inventive systems of the present invention wouldutilize an IP address of the web order to determine which area(s) ofmedia coverage to associate with a customer who placed the particularorder. In some embodiments, the inventive systems of the presentinvention can utilize the area groupings such as DMA (Designated MarketArea) regions which are the geographic areas in the United States inwhich local television viewing is measured by The Nielsen Company. Forexample, a DMA region can be a group of counties that form an exclusivegeographic area in which the home market television stations hold adominance of total hours viewed. In the Nielsen′ example, there are 210DMA regions, covering the entire continental United States, Hawaii, andparts of Alaska.

In some embodiments, the inventive systems of the present invention canthen use the particular geographic area(s) associated with the customerof the web order to further select for a potential match to mediaairings within particular time window(s). For example, in case of usingDMA regions, in some embodiments, the inventive systems of the presentinvention can be configured to select media airings which are (1) localto the customer's local DMA and/or (2) national based airings coveringall or a few DMA regions which includes the customer's local DMA. Forexample, FIG. 5, identifies as highlighted airings that will be removedwhen the customer's DMA is Los Angeles. FIG. 6 also shows anotherexample of filtering out based on customer's geographic location. If anorder is placed in the New York DMA on Saturday, Mar. 14, 2015 at 1 PM,as FIG. 6 shows, in some embodiments, the inventive systems of thepresent invention be configured to select media airings which are:

National Cable airings

Satellite airings

Local airings within the New York DMA.

After the potential media airings are selected based on geographicareas, in some embodiments, as shown in FIG. 7, the inventive systems ofthe present invention can then use at least one financial parameter(e.g., cost per spot (CPS),) to assign a statistical measure (e.g.,weighted probability) of the likelihood that the particular web order isdue to a particular media airing. For example, each probability iscalculated as a % ratio of net media cost (CPS) of a particular airing(e.g., $10,137 for CNBC) to the cost of all airings ($27,700.05). Insome embodiments, the inventive systems of the present invention can useat least one non-financial parameter (e.g., Nielsen Ratings) to assign astatistical measure (e.g., weighted probability) of the likelihood thatthe particular web order is due to a particular media airing. In someembodiments, the inventive systems of the present invention rounds theprobabilities to whole numbers as shown in FIG. 7.

After the statistical measure has been applied, in some embodiments, asshown in FIG. 8, the inventive systems of the present invention cancreate a database of records in which each media airing entry in FIG. 7duplicate X times, where X corresponds to the whole number probabilityassociated with the respective media airing, ending with 100 records intotal in the database, corresponding to 100 percent. In someembodiments, the inventive systems of the present invention can thenutilize a random number generator function to assign a random numberbetween 0 and 1 to each record of the 100 records in the database. FIG.8 shows a snapshot of such database based on FIG. 7's airings. In someembodiments, the inventive systems of the present invention can thenrank 100 records from 1 to 100, where rank 1 is assigned to a recordthat has a random number that is the closest to 1, and so on. Forexample, the highest rank is assigned to the last record in FIG. 8,which has the random number of 0.96. In some embodiments, the inventivesystems of the present invention then attributes the particular weborder to the highest ranked media airing (e.g., CNBC airing at 10:30 AMon Mar. 22, 2015). FIG. 9 shows a snapshot of ranked attributed mediaairings for multiple transactions.

In some embodiments, the inventive systems of the present invention cancontinuously re-run the attribution processes if particularcondition(s)/trigger(s) is/are met. For example, if a web order isattributed to an airing, which is then removed from the database of MARsin a future update from a media agency, any order(s) which matched theremoved airing previously are re-run through the web attribution processto be assigned to a new airing. For example, an airing may be removedfrom the database of MARs because it did not clear, or did not run, orthe offer was decided in future to be non-attributable.

In some embodiments, after the particular web originated activity (e.g.,web order) has been attributed to a particular media airing, theinventive systems of the present invention can utilize the attributedtransaction for further analysis by systems such as described in theU.S. patent application Ser. No. 14/455,826, entitled “METHODS ANDSYSTEMS FOR ANALYZING KEY PERFORMANCE METRICS,” whose specificdisclosures are hereby incorporated herein by reference in theirentirety.

In some embodiments, after the particular web order has been attributedto the particular media airing, the inventive systems of the presentinvention stores this transaction into a specialized database forfurther references and data analysis.

In some embodiments, the inventive systems of the present invention cangenerate various visual real-time updatable reports showing the statusof web attribution process on a periodic basis (e.g., day, week, month,etc.).

In some embodiments, the inventive systems of the present invention cangenerate a cost to acquire, by DMA-based, validation model interactivereport and analysis.

In some embodiments, after the particular web order has been attributedto the particular media airing and when Fulfillment data is available,the inventive systems of the present invention matches/identifies atleast one fulfillment record matching the web attributed order based, atleast in part, on MAR/airing and IP address, and updates its databasewith URL, Customer Name and Address. In some embodiments, the inventivesystems of the present invention, can update the web attributed databased on fulfillment data and utilize the matched record for trackingfulfillment events (e.g., cancellation, future orders, installmentpayment, etc.).

In some embodiments, the inventive systems of the present inventionutilize machine learning feedback to build offer(s) based on web and MARdata.

In some embodiments, the inventive systems of the present inventionutilizes two or more web data sources to attribute the particular weborder to the particular media airing. In some embodiments, the inventivesystems of the present invention utilizes two or more web data sourcesand fulfillment data to attribute the particular web order to theparticular media airing.

Fulfillment Data Feed

In some embodiments, fulfillment data feeds are matched to call centerdata, web data, media data, based on a plurality of fields such as OrderID, Offer ID, Name & Address, and Order Amount. In some embodiments, thefulfillment data is received with a time delay such as 3-5 business daysbehind the call center and/or web data. In some embodiments, to matchthe Call Center Database Record to the Fulfillment Data Feed, theinventive systems of the present invention utilize the match logic thatcan be based on a plurality of the following fields:

Order Date

Zip (e.g., 5 Digits, 9 digits, 11 digits)

Last Name (e.g., first 5 letters)

Order Amount

Street Name (e.g., first 5 characters).

In some embodiments, once Call Center Data and fulfillment data arematched, the inventive systems of the instant invention automaticallyassign tags and create master records in the tagging database.

In some embodiments, the inventive computer systems can host a largenumber of users (e.g., at least 10, at least 100, at least 1,000, atleast 10,000; at least 100,000; at least 1,000,000) and perform a largenumber of concurrent transactions (e.g., at least 1,000, at least10,000; at least 100,000; at least 1,000,000).

In some embodiments, the inventive computer systems are based on ascalable computer and network architecture that incorporates variousstrategies for assessing the data, caching, searching, and databaseconnection pooling. An example of the scalable architecture is anarchitecture that is capable of operating multiple servers. Inembodiments, the computing system in accordance with the instantinvention may include, but not limiting to, one or more programmedcomputers, systems employing distributed networking, or other type ofsystem that might be used to transmit and process electronic data.

FIG. 1 depicts a block diagram of an exemplary system 100 in accordancewith one or more embodiments. System 100 may include one or more userdevices, e.g. user device 120-1, user device 120-2, and user device120-3, network 130, server 150, database 155, software module 165, andserver 180.

The one or more user devices, e.g. user device 120-1, user device 120-2,and user device 120-3, may any type of computing device, including amobile telephone, a laptop, tablet, or desktop computer having, anetbook, a video game device, a pager, a smart phone, an ultra-mobilepersonal computer (UMPC), or a personal data assistant (PDA). The one ormore user devices may run one or more applications, such as Internetbrowsers, mobile applications, voice calls, video games,videoconferencing, and email, among others. The one or more user devicesmay be any combination of computing devices. These devices may becoupled to network 130. Network 130 may provide network access, datatransport and other services to the devices coupled to it. In general,network 130 may include and implement any commonly defined networkarchitectures including those defined by standards bodies, such as theGlobal System for Mobile communication (GSM) Association, the InternetEngineering Task Force (IETF), and the Worldwide Interoperability forMicrowave Access (WiMAX) forum. For example, network 130 may implementone or more of a GSM architecture, a General Packet Radio Service (GPRS)architecture, a Universal Mobile Telecommunications System (UMTS)architecture, and an evolution of UMTS referred to as Long TermEvolution (LTE). Network 130 may, again as an alternative or inconjunction with one or more of the above, implement a WiMAXarchitecture defined by the WiMAX forum. Network 130 may also comprise,for instance, a local area network (LAN), a wide area network (WAN), theInternet, a virtual LAN (VLAN), an enterprise LAN, a layer 3 virtualprivate network (VPN), an enterprise IP network, or any combinationthereof.

Server 150 or server 180 may also be any type of computing devicecoupled to network 130, including but not limited to a personalcomputer, a server computer, a series of server computers, a minicomputer, and a mainframe computer, or combinations thereof. Server 150or server 180 may be a web server (or a series of servers) running anetwork operating system, examples of which may include but are notlimited to Microsoft Windows Server, Novell NetWare, or Linux. Server150 or server 180 may be used for and/or provide cloud and/or networkcomputing. Although not shown in FIG. 1, server 150 and or server 180may have connections to external systems like email, SMS messaging, textmessaging, ad content providers, etc. Any of the features of server 150may be also implemented in server 180 and vice versa.

Database 155 may be any type of database, including a database managedby a database management system (DBMS). A DBMS is typically implementedas an engine that controls organization, storage, management, andretrieval of data in a database. DBMSs frequently provide the ability toquery, backup and replicate, enforce rules, provide security, docomputation, perform change and access logging, and automateoptimization. Examples of DBMSs include Oracle database, IBM DB2,Adaptive Server Enterprise, FileMaker, Microsoft Access, Microsoft SQLServer, MySQL, PostgreSQL, and a NoSQL implementation. A DBMS typicallyincludes a modeling language, data structure, database query language,and transaction mechanism. The modeling language is used to define theschema of each database in the DBMS, according to the database model,which may include a hierarchical model, network model, relational model,object model, or some other applicable known or convenient organization.Data structures can include fields, records, files, objects, and anyother applicable known or convenient structures for storing data. A DBMSmay also include metadata about the data that is stored.

Software module 165 may be a module that is configured to send, process,and receive information at server 150. Software module 165 may provideanother mechanism for sending and receiving data at server 150 besideshandling requests through web server functionalities. Software module165 may send and receive information using any technique for sending andreceiving information between processes or devices including but notlimited to using a scripting language, a remote procedure call, anemail, a tweet, an application programming interface, Simple ObjectAccess Protocol (SOAP) methods, Common Object Request BrokerArchitecture (CORBA), HTTP (Hypertext Transfer Protocol), REST(Representational State Transfer), any interface for software componentsto communicate with each other, using any other known technique forsending information from a one device to another, or any combinationthereof.

Although software module 165 may be described in relation to server 150,software module 165 may reside on any other device. Further, thefunctionality of software module 165 may be duplicated on, distributedacross, and/or performed by one or more other devices, either in wholeor in part.

FIG. 2 depicts an exemplary architecture for implementing a computingdevice 400 in accordance with one or more embodiments, which may be usedto implement any of the computing devices discussed herein, or any othercomputer system or computing device component thereof. It will beappreciated that other devices that can be used with the computingdevice 400, such as a client or a server, may be similarly configured.As illustrated in FIG. 4, computing device 400 may include a bus 410, aprocessor 420, a memory 430, a read only memory (ROM) 440, a storagedevice 450, an input device 460, an output device 470, and acommunication interface 480. Bus 410 may include one or moreinterconnects that permit communication among the components ofcomputing device 400. Processor 420 may include any type of processor,microprocessor, or processing logic that may interpret and executeinstructions (e.g., a field programmable gate array (FPGA)). Processor420 may include a single device (e.g., a single core) and/or a group ofdevices (e.g., multi-core). Memory 430 may include a random accessmemory (RAM) or another type of dynamic storage device that may storeinformation and instructions for execution by processor 420. Memory 430may also be used to store temporary variables or other intermediateinformation during execution of instructions by processor 420.

ROM 440 may include a ROM device and/or another type of static storagedevice that may store static information and instructions for processor420. Storage device 450 may include a magnetic disk and/or optical diskand its corresponding drive for storing information and/or instructions.Storage device 450 may include a single storage device or multiplestorage devices, such as multiple storage devices operating in parallel.Moreover, storage device 450 may reside locally on the computing device400 and/or may be remote with respect to a server and connected theretovia network and/or another type of connection, such as a dedicated linkor channel.

Input device 460 may include any mechanism or combination of mechanismsthat permit an operator to input information to computing device 400,such as a keyboard, a mouse, a touch sensitive display device, amicrophone, a pen-based pointing device, and/or a biometric inputdevice, such as a voice recognition device and/or a finger printscanning device. Output device 470 may include any mechanism orcombination of mechanisms that outputs information to the operator,including a display, a printer, a speaker, etc.

Communication interface 480 may include any transceiver-like mechanismthat enables computing device 400 to communicate with other devicesand/or systems, such as a client, a server, a license manager, a vendor,etc. For example, communication interface 480 may include one or moreinterfaces, such as a first interface coupled to a network and/or asecond interface coupled to a license manager. Alternatively,communication interface 480 may include other mechanisms (e.g., awireless interface) for communicating via a network, such as a wirelessnetwork. In one implementation, communication interface 480 may includelogic to send code to a destination device, such as a target device thatcan include general purpose hardware (e.g., a personal computer formfactor), dedicated hardware (e.g., a digital signal processing (DSP)device adapted to execute a compiled version of a model or a part of amodel), etc.

Computing device 400 may perform certain functions in response toprocessor 420 executing software instructions contained in acomputer-readable medium, such as memory 430. In alternativeembodiments, hardwired circuitry may be used in place of or incombination with software instructions to implement features consistentwith principles of the disclosure. Thus, implementations consistent withprinciples of the disclosure are not limited to any specific combinationof hardware circuitry and software.

Exemplary embodiments may be embodied in many different ways as asoftware component. For example, it may be a stand-alone softwarepackage, a combination of software packages, or it may be a softwarepackage incorporated as a “tool” in a larger software product. It may bedownloadable from a network, for example, a website, as a stand-aloneproduct or as an add-in package for installation in an existing softwareapplication. It may also be available as a client-server softwareapplication, or as a web-enabled software application. It may also beembodied as a software package installed on a hardware device.

Numerous specific details have been set forth to provide a thoroughunderstanding of the embodiments. It will be understood, however, thatthe embodiments may be practiced without these specific details. Inother instances, well-known operations, components and circuits have notbeen described in detail so as not to obscure the embodiments. It can beappreciated that the specific structural and functional details arerepresentative and do not necessarily limit the scope of theembodiments. It is worthy to note that any reference to “one embodiment”or “an embodiment” means that a particular feature, structure, orcharacteristic described in connection with the embodiment is includedin at least one embodiment. The appearances of the phrases “in oneembodiment” or “in some embodiments” in the specification are notnecessarily all referring to the same embodiment.

Although some embodiments may be illustrated and described as comprisingexemplary functional components or modules performing variousoperations, it can be appreciated that such components or modules may beimplemented by one or more hardware components, software components,and/or combination thereof. The functional components and/or modules maybe implemented, for example, by logic (e.g., instructions, data, and/orcode) to be executed by a logic device (e.g., processor). Such logic maybe stored internally or externally to a logic device on one or moretypes of computer-readable storage media.

Some embodiments may comprise an article of manufacture. An article ofmanufacture may comprise a storage medium to store logic. Examples of astorage medium may include one or more types of computer-readablestorage media capable of storing electronic data, including volatilememory or non-volatile memory, removable or non-removable memory,erasable or non-erasable memory, writeable or re-writeable memory, andso forth. Examples of storage media include hard drives, disk drives,solid state drives, and any other tangible storage media.

In some embodiments, the present invention is directed to a computersystem which includes at least the following components: at least onespecifically programmed server; at least one non-transitory webattribution database accessible by the at least one specificallyprogrammed server, where the at least one web attribution database isspecifically programmed to be dedicated for use by the at least onespecifically programmed server; where the at least one specificallyprogrammed server comprises a plurality of modules configured to performat least the following operations: electronically and periodicallyobtaining, over the computer network, by a media data programmedcomputer interface module of the at least one specifically programmedserver, media data from a plurality of computer systems of media datasources, where the media data is associated with a plurality of mediaairings of a plurality creatives; electronically and periodicallyobtaining, over a computer network, by a web data programmed computerinterface module of the at least one specifically programmed server, webtracking transaction data from a computer system of at least one webtracking electronic source; where the web tracking transaction dataincluding web tracking metrics for web originated activities for atleast one website associated with at least one offer of at least onecreative; where web originated activities comprise web orders placed inresponse to the at least one offer associated with the at least onecreative; for each web order record in the transactional web data: basedon an item identifier of at least one item and a price of the at leastone item corresponding to a particular web order corresponding to suchweb order record, determining, the at least one specifically programmedserver, at least one particular offer associated with the particular weborder, based on the at least one particular offer, determining, the atleast one specifically programmed server, a length of a creative whichhas used for promoting the at least one item; based on the particularoffer, identifying, the at least one specifically programmed server, asubset of media agency records in the media data which are potentiallyattributable to such particular web order; adjusting, the at least onespecifically programmed server, a time of airing for each record in thesubset of media agency records based on at least one of: i) apredetermined uniform time zone, and ii) an IP address associated withthe web order, and iii) a geographic location of a web host at which theparticular web order was placed; based on the length of the creative,selecting, the at least one specifically programmed server, a firstsubgroup of media agency records from the subset of media agencyrecords, where the length of the creative corresponds to a predeterminetime window, where the predetermined time window ends at the time of theparticular web order, and continues in the past for a predetermined timeduration; based on an IP address of the particular web order from thetransactional web data, selecting, the at least one specificallyprogrammed server, a second subgroup of media agency records from thefirst subgroup of media agency records, where the second subgroup ofmedia agency records correspond to media airings shown in a geographiclocality of the particular web order; determining, by the at least onespecifically programmed server, for each media airing of the secondsubgroup, a probability of attribution based on cost of such mediaairing or viewership rating; based on the probability of attribution,duplicating, by the at least one specifically programmed server, aparticular media airing record of the second subgroup X times in thededicated database to obtain a third subgroup, where X is a whole numberbased on rounding the probability of attribution; assigning, by the atleast one specifically programmed server, to each record in the thirdsubgroup a random value within a predetermined number range between Y1and Y2, where Y2 is larger than Y1; based on the random value, ranking,by the at least one specifically programmed server, each record in thethird subgroup so that a particular media airing having the random valuewhich is the closest to Y2 is assigned the highest rank; attributing, bythe at least one specifically programmed server, the particular weborder to the particular media airing having the highest rank; anddisplaying, the at least one specifically programmed server, utilizingat least one graphical user interface, a real time updatable webattribution report.

In some embodiments, the at least one specifically programmed server isfurther configured to: electronically and real-time obtain, by afulfillment data programmed computer interface module of the at leastone specifically programmed server, from a computer system of at leastone fulfillment electronic source, fulfillment transaction data; wherethe fulfillment transaction data including a plurality of at leastthousand fulfillment records associated a plurality of at least thousandfulfillment transactions for the web orders; where each fulfillmentrecord identifies each fulfillment transaction being associated with aparticular web order; and matching, in real-time, records between webrecords and fulfillment records based, at least in part, on: i) an orderdate, ii) a 5 digit Zip code, iii) a last name, iv) an order amount, andv) optionally, a street name.

In some embodiments, the at least one web tracking electronic source isselected from the group consisting of: Piwik, Google Analytics, andOmniture.

In some embodiments, the length of the creative corresponds to thepredetermine time window based on the following rules: i) when thelength of the creative is between 15 and 30 seconds, the predeterminedtime window is 30 minutes, ii) when the length of the creative isbetween 60 and 120 seconds, the predetermined time window is 2 hours,iii) when the length of the creative is 5 minutes, the predeterminedtime window is 4 hours, and iv) when the length of the creative is 28minutes and 30 seconds, the predetermined time window is 8 hours. Insome embodiments, Y1 is 0, and Y2 is 1. In some embodiments, the randomvalue is generated by a random value generator. In some embodiments, thepredetermined time zone is selected from the group consisting of: U.S.Eastern time zone, U.S. Central time zone, and U.S. Western time zone.

In some embodiments, the media airing is an airing which is selectedfrom the group consisting of: a television station airing, a radiostation airing, a video-on-demand airing, a web-promoted offer airing,and a mobile message airing. In some embodiments, the viewership ratingis Nielsen rating.

In some embodiments, the present invention is directed to acomputer-implemented method which includes at least the following steps:electronically and periodically obtaining, over the computer network, bya media data programmed computer interface module of the at least onespecifically programmed server, media data from a plurality of computersystems of media data sources, where the media data is associated with aplurality of media airings of a plurality creatives; electronically andperiodically obtaining, over a computer network, by a web dataprogrammed computer interface module of the at least one specificallyprogrammed server, web tracking transaction data from a computer systemof at least one web tracking electronic source; where the web trackingtransaction data including web tracking metrics for web originatedactivities for at least one website associated with at least one offerof at least one creative; where web originated activities comprise weborders placed in response to the at least one offer associated with theat least one creative; for each web order record in the transactionalweb data: based on an item identifier of at least one item and a priceof the at least one item corresponding to a particular web ordercorresponding to such web order record, determining, the at least onespecifically programmed server, at least one particular offer associatedwith the particular web order, based on the at least one particularoffer, determining, the at least one specifically programmed server, alength of a creative which has used for promoting the at least one item;based on the particular offer, identifying, the at least onespecifically programmed server, a subset of media agency records in themedia data which are potentially attributable to such particular weborder; adjusting, the at least one specifically programmed server, atime of airing for each record in the subset of media agency recordsbased on at least one of: i) a predetermined uniform time zone, and ii)an IP address associated with the web order, and iii) a geographiclocation of a web host at which the particular web order was placed;based on the length of the creative, selecting, the at least onespecifically programmed server, a first subgroup of media agency recordsfrom the subset of media agency records, where the length of thecreative corresponds to a predetermine time window, where thepredetermined time window ends at the time of the particular web order,and continues in the past for a predetermined time duration; based on anIP address of the particular web order from the transactional web data,selecting, the at least one specifically programmed server, a secondsubgroup of media agency records from the first subgroup of media agencyrecords, where the second subgroup of media agency records correspond tomedia airings shown in a geographic locality of the particular weborder; determining, by the at least one specifically programmed server,for each media airing of the second subgroup, a probability ofattribution based on cost of such media airing or viewership rating;based on the probability of attribution, duplicating, by the at leastone specifically programmed server, a particular media airing record ofthe second subgroup X times in the dedicated database to obtain a thirdsubgroup, where X is a whole number based on rounding the probability ofattribution; assigning, by the at least one specifically programmedserver, to each record in the third subgroup a random value within apredetermined number range between Y1 and Y2, where Y2 is larger thanY1; based on the random value, ranking, by the at least one specificallyprogrammed server, each record in the third subgroup so that aparticular media airing having the random value which is the closest toY2 is assigned the highest rank; attributing, by the at least onespecifically programmed server, the particular web order to theparticular media airing having the highest rank; and displaying, the atleast one specifically programmed server, utilizing at least onegraphical user interface, a real time updatable web attribution report.

It also is to be appreciated that the described embodiments illustrateexemplary implementations, and that the functional components and/ormodules may be implemented in various other ways which are consistentwith the described embodiments. Furthermore, the operations performed bysuch components or modules may be combined and/or separated for a givenimplementation and may be performed by a greater number or fewer numberof components or modules.

While various exemplary embodiments have been described above, it shouldbe understood that they have been presented by way of example only, andnot limitation. Thus, the breadth and scope of the present disclosureshould not be limited by any of the above-described exemplaryembodiments.

What is claimed is:
 1. A computer system, comprising: at least onespecifically programmed server; at least one non-transitory webattribution database accessible by the at least one specificallyprogrammed server, wherein the at least one web attribution database isspecifically programmed to be dedicated for use by the at least onespecifically programmed server; wherein the at least one specificallyprogrammed server comprises a plurality of modules configured to performat least the following operations: electronically and periodicallyobtaining, over the computer network, by a media events data programmedcomputer interface module of the at least one specifically programmedserver, media events data from a plurality of computer systems of mediaevents originated sources, wherein the media events data is associatedwith a plurality of media events related to a plurality of creatives;electronically and periodically obtaining, over a computer network, by aweb data programmed computer interface module of the at least onespecifically programmed server, web tracking transaction data from atleast one computer system of at least one web tracking electronicsource; wherein the web tracking transaction data comprising webtracking metrics for web originated activities for at least one websiteassociated with at least one media event associated with at least onecreative; wherein the web originated activities comprise activities donein response to the at least one media event associated with the at leastone creative; for each web activity record in the transactional webdata: based on an item identifier of at least one item and a price ofthe at least one item corresponding to a particular web activitycorresponding to such web activity record, determining, the at least onespecifically programmed server, at least one particular media eventassociated with the particular web activity, based on the at least oneparticular media event, determining, the at least one specificallyprogrammed server, a length of a creative; based on the particular mediaevent, identifying, the at least one specifically programmed server, asubset of media events records in the media events data which arepotentially attributable to such particular web activity; adjusting, theat least one specifically programmed server, a time of at least onemedia event for each record in the subset of media events records basedon at least one of: i) a predetermined uniform time zone, and ii) an IPaddress associated with the particular web activity, and iii) ageographic location of a web host at which the particular web activitywas placed; based on the length of the creative, selecting, the at leastone specifically programmed server, a first subgroup of media eventsrecords from the subset of media events records, wherein the length ofthe creative corresponds to a predetermine time window, wherein thepredetermined time window ends at the time of the web activity, andcontinues in the past for a predetermined time duration; based on an IPaddress of the web activity from the transactional web data, selecting,the at least one specifically programmed server, a second subgroup ofmedia events records from the first subgroup of media events records,wherein the second subgroup of media events records correspond to mediaevents shown in a geographic locality of the particular web activity;determining, by the at least one specifically programmed server, foreach media event of the second subgroup, a probability of attributionbased on cost of such particular media event or viewership rating; basedon the probability of attribution, duplicating, by the at least onespecifically programmed server, a particular media event record of thesecond subgroup X times in the dedicated database to obtain a thirdsubgroup, wherein X is a whole number based on rounding the probabilityof attribution; assigning, by the at least one specifically programmedserver, to each record in the third subgroup a random value within apredetermined number range between Y1 and Y2, wherein Y2 is larger thanY1; based on the random value, ranking, by the at least one specificallyprogrammed server, each record in the third subgroup so that aparticular media event having the random value which is the closest toY2 is assigned the highest rank; attributing, by the at least onespecifically programmed server, the particular web activity to theparticular media event having the highest rank; and displaying, the atleast one specifically programmed server, utilizing at least onegraphical user interface, a real time updatable web attribution report.2. The computer system of claim 1, wherein the web originated activitiesare web originated orders; wherein the at least one specificallyprogrammed server is further configured to: electronically and real-timeobtain, by a fulfillment data programmed computer interface module ofthe at least one specifically programmed server, from a computer systemof at least one fulfillment electronic source, fulfillment transactiondata; wherein the fulfillment transaction data comprising a plurality ofat least thousand fulfillment records associated a plurality of at leastthousand fulfillment transactions for the web originated orders; whereineach fulfillment record identifies each fulfillment transaction beingassociated with a particular web originated order; and matching, inreal-time, records between web records and fulfillment records based, atleast in part, on: i) an order date, ii) a Zip code, iii) a last name,iv) an order amount, and v) optionally, a street name.
 3. The computersystem of claim 1, wherein the at least one web tracking electronicsource is selected from the group consisting of: Piwik, GoogleAnalytics, and Omniture.
 4. The computer system of claim 1, wherein thelength of the creative corresponds to the predetermine time window basedon the following rules: i) when the length of the creative is between 15and 30 seconds, the predetermined time window is Z1 value; ii) when thelength of the creative is between 60 and 120 seconds, the predeterminedtime window is Z2 value; iii) when the length of the creative is 5minutes, the predetermined time window is Z3 value; iv) when the lengthof the creative is 28 minutes and 30 seconds, the predetermined timewindow is Z4 value; v) wherein the Z1 value is distinct from at leastone of the Z2 value, the Z3 value, and the Z4 value; vi) wherein the Z2value is distinct from at least one of the Z1 value, the Z3 value, andthe Z4 value; vii) wherein the Z3 value is distinct from at least one ofthe Z1 value, the Z2 value, and the Z4 value; and viii) wherein the Z4value is distinct from at least one of the Z1 value, the Z2 value, andthe Z3 value.
 5. The computer system of claim 1, wherein Y1 is 0, and Y2is
 1. 6. The computer system of claim 1, wherein the random value isgenerated by a random value generator.
 7. The computer system of claim1, wherein the predetermined time zone is selected from the groupconsisting of: U.S. Eastern time zone, U.S. Central time zone, and U.S.Western time zone.
 8. The computer system of claim 1, wherein theparticular media event is an airing which is selected from the groupconsisting of: a television station airing, a radio station airing, avideo-on-demand airing, a web-promoted offer airing, and a mobilemessage airing.
 9. The computer system of claim 8, wherein theviewership rating is Nielsen rating.
 10. A computer-implemented method,comprising: electronically and periodically obtaining, over a computernetwork, by a media events data programmed computer interface module ofat least one specifically programmed server, media events data from aplurality of computer systems of media events originated data sources,wherein the media events data is associated with a plurality of mediaevents related to a plurality of creatives; electronically andperiodically obtaining, over the computer network, by a web dataprogrammed computer interface module of the at least one specificallyprogrammed server, web tracking transaction data from at least onecomputer system of at least one web tracking electronic source; whereinthe web tracking transaction data comprising web tracking metrics forweb originated activities for at least one website associated with atleast one media event associated with at least one creative; wherein weboriginated activities comprise activities done in response to the atleast one media event associated with the at least one creative; foreach web activity record in the transactional web data: based on an itemidentifier of at least one item and a price of the at least one itemcorresponding to a particular web activity corresponding to such webactivity record, determining, the at least one specifically programmedserver, at least one particular media event associated with theparticular web activity, based on the at least one particular mediaevent, determining, the at least one specifically programmed server, alength of a creative; based on the at least one particular media event,identifying, the at least one specifically programmed server, a subsetof media events records in the media events data which are potentiallyattributable to the particular web activity; adjusting, the at least onespecifically programmed server, a time of at least one media event foreach record in the subset of media events records based on at least oneof: i) a predetermined uniform time zone, and ii) an IP addressassociated with the web activity, and iii) a geographic location of aweb host at which the particular web activity was placed; based on thelength of the creative, selecting, the at least one specificallyprogrammed server, a first subgroup of media events records from thesubset of media events records, wherein the length of the creativecorresponds to a predetermine time window, wherein the predeterminedtime window ends at the time of the particular web activity, andcontinues in the past for a predetermined time duration; based on an IPaddress of the particular web activity from the transactional web data,selecting, the at least one specifically programmed server, a secondsubgroup of media events records from the first subgroup of media eventsrecords, wherein the second subgroup of media events records correspondto media events shown in a geographic locality of the particular webactivity; determining, by the at least one specifically programmedserver, for each media event of the second subgroup, a probability ofattribution based on cost of such media event or viewership rating;based on the probability of attribution, duplicating, by the at leastone specifically programmed server, a particular media event record ofthe second subgroup X times in the dedicated database to obtain a thirdsubgroup, wherein X is a whole number based on rounding the probabilityof attribution; assigning, by the at least one specifically programmedserver, to each record in the third subgroup a random value within apredetermined number range between Y1 and Y2, wherein Y2 is larger thanY1; based on the random value, ranking, by the at least one specificallyprogrammed server, each record in the third subgroup so that aparticular media event having the random value which is the closest toY2 is assigned the highest rank; attributing, by the at least onespecifically programmed server, the web activity to the particular mediaevent having the highest rank; and displaying, the at least onespecifically programmed server, utilizing at least one graphical userinterface, a real time updatable web attribution report.
 11. The methodof claim 10, further comprising: electronically and real-time obtaining,by a fulfillment data programmed computer interface module of the atleast one specifically programmed server, from a computer system of atleast one fulfillment electronic source, fulfillment transaction data;wherein the web originated activities are web originated orders; whereinthe fulfillment transaction data comprising a plurality of at leastthousand fulfillment records associated a plurality of at least thousandfulfillment transactions for the web originated orders; wherein eachfulfillment record identifies each fulfillment transaction beingassociated with a particular web originated order; and matching, inreal-time, records between web records and fulfillment records based, atleast in part, on: i) an order date, ii) a Zip code, iii) a last name,iv) an order amount, and v) optionally, a street name.
 12. The method ofclaim 10, wherein the at least one web tracking electronic source isselected from the group consisting of: Piwik, Google Analytics, andOmniture.
 13. The method of claim 10, wherein the length of the creativecorresponds to the predetermine time window based on the followingrules: i) when the length of the creative is between 15 and 30 seconds,the predetermined time window is Z1 value; ii) when the length of thecreative is between 60 and 120 seconds, the predetermined time window isZ2 value; iii) when the length of the creative is 5 minutes, thepredetermined time window is Z3 value; iv) when the length of thecreative is 28 minutes and 30 seconds, the predetermined time window isZ4 value; v) wherein the Z1 value is distinct from at least one of theZ2 value, the Z3 value, and the Z4 value; vi) wherein the Z2 value isdistinct from at least one of the Z1 value, the Z3 value, and the Z4value; vii) wherein the Z3 value is distinct from at least one of the Z1value, the Z2 value, and the Z4 value; and viii) wherein the Z4 value isdistinct from at least one of the Z1 value, the Z2 value, and the Z3value.
 14. The method of claim 10, wherein Y1 is 0, and Y2 is
 1. 15. Themethod of claim 10, wherein the random value is generated by a randomvalue generator.
 16. The method of claim 10, wherein the predeterminedtime zone is selected from the group consisting of: U.S. Eastern timezone, U.S. Central time zone, and U.S. Western time zone.
 17. The methodof claim 10, wherein the particular media event is an airing which isselected from the group consisting of: a television station airing, aradio station airing, a video-on-demand airing, a web-promoted offerairing, and a mobile message airing.
 18. The method of claim 17, whereinthe viewership rating is Nielsen rating.